Modeling to Engineering and Failure Times Data: Using the Marshall–Olkin Extended Exponential Distribution
In this article, we study and introduce the Marshall–Olkin extended exponential (MO‐ExE) distribution, a novel three‐parameter life expectancy distribution. The new model is characterized by high adaptability in data analysis. Various mathematical properties, including ordinary moments, moment‐generating functions (MGFs), and conditional moments (CMs) of the new suggested model, were computed. The model parameters are estimated using the maximum likelihood method. A simulation study is evaluated to demonstrate the behavior of the parameter model. In the final analysis, we demonstrate the significance of the novel model by examining practical data applications, thus, showing the adaptability and potential of the MO‐ExE model.
Authors
- Suleman Nasiru (ORCID: https://orcid.org/0000-0001-6652-4251)
- Ibrahim E. Ragab (ORCID: https://orcid.org/0000-0001-6087-8649)
- Mohammed Elgarhy (ORCID: https://orcid.org/0000-0002-1333-3862)
- Mustapha Muhammad (ORCID: https://orcid.org/0000-0003-0329-5898)
- Najwan Alsadat (ORCID: https://orcid.org/0000-0001-8884-8281)
Institutions
- King Saud University (SA)
- Guangdong University of Petrochemical Technology (CN)
- Egyptian Institute of Alexandria Academy for Administration & Accounting (EG)
- High Institute for Management Sciences (EG)
- C.K. Tedam University of Technology and Applied Sciences (GH)
Publication Details
- Journal
- Advances in Mathematical Physics
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1155/admp/6659119
- Citations
- 1
- Primary Topic
- Statistical Distribution Estimation and Applications
- Type
- article
- Field-Weighted Citation Impact
- 2.63
Funders
- King Saud University